Abstract | OBJECTIVES: Medical and surgical intensive care unit patients represent two different populations and require different treatment approaches. The aim of this study was to investigate the parameters associated with mortality in medical and surgical intensive care units. METHODS: This was a prospective cohort study of adult patients admitted to a medical and surgical intensive care unit teaching hospital over an 11-month period. Factors associated with mortality were explored using logistic regression analysis. RESULTS: In total, 827 admissions were observed, and 525 patients >18 years old and with a length of stay >24 h were analyzed. Of these patients, 227 were in the medical and 298 were in the surgical intensive care unit. The surgical patients were older (p<0.01) and had shorter lengths of stay (p<0.01). The mortality in the intensive care unit (35.1 vs. 26.2, p = 0.02) and hospital (48.8 vs. 35.5, p<0.01) was higher for medical patients. For patients in the surgical intensive care unit, death was independently associated with the need for mechanical ventilation, prognostic score (SAPS II), community-acquired infection, nosocomial infection, and intensive care unit-acquired infection. For patients in the medical intensive care unit, death was independently associated with the need for mechanical ventilation and prognostic score. CONCLUSIONS:
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Authors | Carlos Toufen Jr, Suelene Aires Franca, Valdelis N Okamoto, João Marcos Salge, Carlos Roberto Ribeiro Carvalho |
Journal | Clinics (Sao Paulo, Brazil)
(Clinics (Sao Paulo))
Vol. 68
Issue 8
Pg. 1103-8
( 2013)
ISSN: 1980-5322 [Electronic] United States |
PMID | 24037005
(Publication Type: Journal Article, Observational Study)
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Topics |
- Adult
- Aged
- Brazil
(epidemiology)
- Critical Care
(statistics & numerical data)
- Cross Infection
(mortality)
- Female
- Hospital Mortality
- Humans
- Intensive Care Units
(statistics & numerical data)
- Kaplan-Meier Estimate
- Length of Stay
(statistics & numerical data)
- Logistic Models
- Male
- Middle Aged
- Outcome Assessment, Health Care
- Patient Admission
(statistics & numerical data)
- Prospective Studies
- Risk Factors
- Time Factors
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